import os
from collections.abc import Generator

import pytest

from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
from core.model_runtime.entities.message_entities import (
    AssistantPromptMessage,
    ImagePromptMessageContent,
    PromptMessageTool,
    SystemPromptMessage,
    TextPromptMessageContent,
    UserPromptMessage,
)
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.azure_openai.llm.llm import AzureOpenAILargeLanguageModel
from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock


@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
def test_validate_credentials_for_chat_model(setup_openai_mock):
    model = AzureOpenAILargeLanguageModel()

    with pytest.raises(CredentialsValidateFailedError):
        model.validate_credentials(
            model='gpt35',
            credentials={
                'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
                'openai_api_key': 'invalid_key',
                'base_model_name': 'gpt-35-turbo'
            }
        )

    model.validate_credentials(
        model='gpt35',
        credentials={
            'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
            'openai_api_key': os.environ.get('AZURE_OPENAI_API_KEY'),
            'base_model_name': 'gpt-35-turbo'
        }
    )

@pytest.mark.parametrize('setup_openai_mock', [['completion']], indirect=True)
def test_validate_credentials_for_completion_model(setup_openai_mock):
    model = AzureOpenAILargeLanguageModel()

    with pytest.raises(CredentialsValidateFailedError):
        model.validate_credentials(
            model='gpt-35-turbo-instruct',
            credentials={
                'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
                'openai_api_key': 'invalid_key',
                'base_model_name': 'gpt-35-turbo-instruct'
            }
        )

    model.validate_credentials(
        model='gpt-35-turbo-instruct',
        credentials={
            'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
            'openai_api_key': os.environ.get('AZURE_OPENAI_API_KEY'),
            'base_model_name': 'gpt-35-turbo-instruct'
        }
    )

@pytest.mark.parametrize('setup_openai_mock', [['completion']], indirect=True)
def test_invoke_completion_model(setup_openai_mock):
    model = AzureOpenAILargeLanguageModel()

    result = model.invoke(
        model='gpt-35-turbo-instruct',
        credentials={
            'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
            'openai_api_key': os.environ.get('AZURE_OPENAI_API_KEY'),
            'base_model_name': 'gpt-35-turbo-instruct'
        },
        prompt_messages=[
            UserPromptMessage(
                content='Hello World!'
            )
        ],
        model_parameters={
            'temperature': 0.0,
            'max_tokens': 1
        },
        stream=False,
        user="abc-123"
    )

    assert isinstance(result, LLMResult)
    assert len(result.message.content) > 0

@pytest.mark.parametrize('setup_openai_mock', [['completion']], indirect=True)
def test_invoke_stream_completion_model(setup_openai_mock):
    model = AzureOpenAILargeLanguageModel()

    result = model.invoke(
        model='gpt-35-turbo-instruct',
        credentials={
            'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
            'openai_api_key': os.environ.get('AZURE_OPENAI_API_KEY'),
            'base_model_name': 'gpt-35-turbo-instruct'
        },
        prompt_messages=[
            UserPromptMessage(
                content='Hello World!'
            )
        ],
        model_parameters={
            'temperature': 0.0,
            'max_tokens': 100
        },
        stream=True,
        user="abc-123"
    )

    assert isinstance(result, Generator)

    for chunk in result:
        assert isinstance(chunk, LLMResultChunk)
        assert isinstance(chunk.delta, LLMResultChunkDelta)
        assert isinstance(chunk.delta.message, AssistantPromptMessage)
        assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True

@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
def test_invoke_chat_model(setup_openai_mock):
    model = AzureOpenAILargeLanguageModel()

    result = model.invoke(
        model='gpt35',
        credentials={
            'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
            'openai_api_key': os.environ.get('AZURE_OPENAI_API_KEY'),
            'base_model_name': 'gpt-35-turbo'
        },
        prompt_messages=[
            SystemPromptMessage(
                content='You are a helpful AI assistant.',
            ),
            UserPromptMessage(
                content='Hello World!'
            )
        ],
        model_parameters={
            'temperature': 0.0,
            'top_p': 1.0,
            'presence_penalty': 0.0,
            'frequency_penalty': 0.0,
            'max_tokens': 10
        },
        stop=['How'],
        stream=False,
        user="abc-123"
    )

    assert isinstance(result, LLMResult)
    assert len(result.message.content) > 0

    for chunk in model._llm_result_to_stream(result):
        assert isinstance(chunk, LLMResultChunk)
        assert isinstance(chunk.delta, LLMResultChunkDelta)
        assert isinstance(chunk.delta.message, AssistantPromptMessage)
        assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True

@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
def test_invoke_stream_chat_model(setup_openai_mock):
    model = AzureOpenAILargeLanguageModel()

    result = model.invoke(
        model='gpt35',
        credentials={
            'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
            'openai_api_key': os.environ.get('AZURE_OPENAI_API_KEY'),
            'base_model_name': 'gpt-35-turbo'
        },
        prompt_messages=[
            SystemPromptMessage(
                content='You are a helpful AI assistant.',
            ),
            UserPromptMessage(
                content='Hello World!'
            )
        ],
        model_parameters={
            'temperature': 0.0,
            'max_tokens': 100
        },
        stream=True,
        user="abc-123"
    )

    assert isinstance(result, Generator)

    for chunk in result:
        assert isinstance(chunk, LLMResultChunk)
        assert isinstance(chunk.delta, LLMResultChunkDelta)
        assert isinstance(chunk.delta.message, AssistantPromptMessage)
        if chunk.delta.finish_reason is not None:
            assert chunk.delta.usage is not None
            assert chunk.delta.usage.completion_tokens > 0

@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
def test_invoke_chat_model_with_vision(setup_openai_mock):
    model = AzureOpenAILargeLanguageModel()

    result = model.invoke(
        model='gpt-4v',
        credentials={
            'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
            'openai_api_key': os.environ.get('AZURE_OPENAI_API_KEY'),
            'base_model_name': 'gpt-4-vision-preview'
        },
        prompt_messages=[
            SystemPromptMessage(
                content='You are a helpful AI assistant.',
            ),
            UserPromptMessage(
                content=[
                    TextPromptMessageContent(
                        data='Hello World!',
                    ),
                    ImagePromptMessageContent(
                        data=''
                    )
                ]
            )
        ],
        model_parameters={
            'temperature': 0.0,
            'max_tokens': 100
        },
        stream=False,
        user="abc-123"
    )

    assert isinstance(result, LLMResult)
    assert len(result.message.content) > 0

@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
def test_invoke_chat_model_with_tools(setup_openai_mock):
    model = AzureOpenAILargeLanguageModel()

    result = model.invoke(
        model='gpt-35-turbo',
        credentials={
            'openai_api_base': os.environ.get('AZURE_OPENAI_API_BASE'),
            'openai_api_key': os.environ.get('AZURE_OPENAI_API_KEY'),
            'base_model_name': 'gpt-35-turbo'
        },
        prompt_messages=[
            SystemPromptMessage(
                content='You are a helpful AI assistant.',
            ),
            UserPromptMessage(
                content="what's the weather today in London?",
            )
        ],
        model_parameters={
            'temperature': 0.0,
            'max_tokens': 100
        },
        tools=[
            PromptMessageTool(
                name='get_weather',
                description='Determine weather in my location',
                parameters={
                    "type": "object",
                    "properties": {
                        "location": {
                            "type": "string",
                            "description": "The city and state e.g. San Francisco, CA"
                        },
                        "unit": {
                            "type": "string",
                            "enum": [
                                "c",
                                "f"
                            ]
                        }
                    },
                    "required": [
                        "location"
                    ]
                }
            ),
            PromptMessageTool(
                name='get_stock_price',
                description='Get the current stock price',
                parameters={
                    "type": "object",
                    "properties": {
                        "symbol": {
                            "type": "string",
                            "description": "The stock symbol"
                        }
                    },
                    "required": [
                        "symbol"
                    ]
                }
            )
        ],
        stream=False,
        user="abc-123"
    )

    assert isinstance(result, LLMResult)
    assert isinstance(result.message, AssistantPromptMessage)
    assert len(result.message.tool_calls) > 0


def test_get_num_tokens():
    model = AzureOpenAILargeLanguageModel()

    num_tokens = model.get_num_tokens(
        model='gpt-35-turbo-instruct',
        credentials={
            'base_model_name': 'gpt-35-turbo-instruct'
        },
        prompt_messages=[
            UserPromptMessage(
                content='Hello World!'
            )
        ]
    )

    assert num_tokens == 3

    num_tokens = model.get_num_tokens(
        model='gpt35',
        credentials={
            'base_model_name': 'gpt-35-turbo'
        },
        prompt_messages=[
            SystemPromptMessage(
                content='You are a helpful AI assistant.',
            ),
            UserPromptMessage(
                content='Hello World!'
            )
        ]
    )

    assert num_tokens == 21
